Method for color matching

ABSTRACT

The invention relates to a method for matching the color of a dry color shade standard, said method comprising the steps of A) Measuring the dry color shade standard, B) Calculating a recipe for the dry color shade standard, C) Generating a virtual wet color shade standard based on the recipe for the dry color shade standard calculated in step B), wherein the virtual wet color shade standard is generated with wet characterization data and D) Matching the virtual wet color shade standard. The method can be used for elaboration of color shades and batch adjustment in production of paints.

FIELD OF INVENTION

The invention relates to a method for matching the color of a colorshade standard. The process has applications in the field ofcolor-imparting and special-effect-imparting surface coatings, inparticular in automotive coatings. It can be used in color laboratoriesor refinish body shops, in particular in matching color shades ofunknown pigmentation, as well as in production of paints in matchingpaint batches to a defined color shade standard.

DESCRIPTION OF RELATED ART

In the paint industry the development of colors for the automotiveindustry in general is a complex, time-consuming, and expensive process.The complexity of a color matching process stems from the fact thatcolor measurement data, characterisation data for every paint line inquestion, and historical paint formulations have to be dealt with. Inorder to be competitive highly efficient methods have to be utilised incolor development processes in coloristic laboratory, productionenvironment, and refinish applications in body-shops. The usage ofinstrumental tools is a prerequisite to efficiently matching colorshades within tight tolerances frequently specified by customers ofpaint manufacturers.

The matching process of colors is an iterative multi-step procedure,where in a first step a given standard of unknown pigmentation ismatched in a chosen paint quality by means of a recipe calculationprogram. In a standard procedure the obtained recipe is mixed,sprayed-out, and dried in an oven at elevated temperatures required bythe chemistry of the paint quality. If the final result meets the targetof the standard within tolerance, the color matching process isfinished. However, if the residual color difference between standard andsample exceeds the specified tolerance, the sprayed-out recipe has to bemeasured and instrumentally corrected. The corrected recipe again has tobe sprayed-out and dried and assessed. These steps have to be repeatedas long as the sample formulation does not meet the specified targetarea of the standard.

The current color development or batch shading processes extensivelymake use of sprayed-out panels at each correction step. Only in thosecases where a wet standard is available, e.g. in the production area,wet color measurement technology is used for shading purposes. In colordevelopment typically carried out in coloristic laboratories to match astandard of unknown pigmentation, dry panels have to be produced at eachcorrection and approval step, since no wet standard is available. Thestep of spraying out panels is much more expensive and time consumingthan performing a wet color measurement. In case of solid colors theaverage number of correction steps is of the order of 3-4, while in caseof gonioapparent colors about 8 correction steps have to be expected onthe average. Therefore, it would be highly desirable to make the entirecolor development process more efficient.

The objective of the present invention was therefore to improve theefficiency of shading processes. In particular the objective of thepresent invention was to provide a time and cost-saving method formatching reference color formulations to a defined dry color shadestandard.

SUMMARY OF THE INVENTION

The present invention describes a method for matching the color of a drycolor shade standard by defining a virtual wet standard which can beused in color development or batch shading processes to switch from adry to a wet target.

The present invention is directed to a method for matching the color ofa dry color shade standard, said method comprising the steps of:

A) Measuring the dry color shade standard,

B) Calculating a recipe for the dry color shade standard or identifyinga matching recipe for the dry color shade standard, for example, from adatabase,

C) Generating a virtual wet color shade standard based on the recipe forthe dry color shade standard calculated or identified in step B),wherein the virtual wet color shade standard is generated with wetcharacterisation data and

D) Matching the virtual wet color shade standard.

According to one embodiment the method, in particular step D), furthercomprises the steps of:

E) Preparing a paint composition according to the recipe for the drycolor shade standard calculated or identified in step B),

F) Measuring the liquid paint composition prepared in step E) and

G) Assessing the quality of match by comparing the measurement result ofstep F) with the virtual wet standard generated in step C).

According to a further embodiment the method further comprising thesteps of:

H) If the liquid paint composition prepared in step E) is not within arequested tolerance, calculating a corrected recipe for said liquidpaint composition,

I) Preparing a paint composition according to the corrected recipe forthe liquid paint composition calculated in step H),

J) Measuring the liquid paint composition prepared in step I) and

K) Assessing the quality of match by comparing the measurement result ofstep J) with the virtual wet standard generated in step C) and

L) Repeating steps H) to K) until the liquid paint composition is withina requested tolerance.

According to a further embodiment The method further comprising thesteps of:

M) If the liquid paint composition prepared in step E) or I) is within arequested tolerance, applying the paint composition prepared in step E)or I) to a substrate and drying the paint composition,

N) Assessing the quality of match by comparing the dried paintcomposition with the dry color shade standard,

O) Calculating a corrected recipe for the dried paint composition, ifthe dried paint composition is not within a requested tolerance,

P) Preparing a paint composition according to the corrected recipe forthe dried paint composition calculated in step O),

Q) Applying the paint composition prepared in step P) to a substrate anddrying the paint composition,

R) Assessing the quality of match by comparing the dried paintcomposition with the dry color shade standard, and

S) Repeating steps O) to R) until the dried paint composition is withina requested tolerance.

It goes without saying that the method of the present invention isapplicable if the first tinting step in a color matching process doesn'tlead to an acceptable result, i.e., if the sprayed out and dried paintor the liquid paint formulated on the basis of the identified orcalculated recipe for the color shade standard doesn't match thecorresponding color shade standard and the difference is not acceptable.It also goes without saying that the method of the present inventionincludes several repeating steps as long as the prepared wet or drypaint is not within a requested tolerance compared with the virtual wetstandard or the dry color shade standard.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic flow diagram of a standard color developmentprocess using dry panels.

FIG. 2 is a schematic flow diagram of the process of the presentinvention combining steps with dry panels and steps with liquid paint.

FIG. 3 shows the reflectance spectra of a measured standard (FordGentian Blue; closed circles), of the corresponding predicted formula(open circles), and of the measured sprayed-out on-load panel of thepredicted formula (open triangles).

FIG. 4 shows an example for the new colour development process accordingto the invention. The left diagram displays the measured dry target(colour shade RAL 2003) and the optimised formula of a standard recipecalculation procedure. The right diagram depicts the calculated virtualwet standard in comparison to the true physical wet standard.

FIG. 5 shows the performance of the new colour development process forcolour standard 2003 of the RAL 841-GL system. Colour development hasbeen carried out in the wet against the virtual wet target. The processterminates after the second hit. Along with the wet colour developmentdata at each correction step corresponding residual colour differencesof each wet sample to the physical wet target and the sprayed-out panelsagainst the dry standard are displayed.

DETAILED DESCRIPTION OF THE EMBODIMENTS

The invention will be explained in greater detail below.

The term “reflection spectrum” shall mean reflection spectrum in case ofsolid color shades and reflection surface in case of special effectcolor shades.

Colorant system should be understood to mean any system of absorptionpigments and/or special-effect pigments comprising all pigments whichshall be used for the production or formulation of paints. The numberand choice of pigment components are not subject to restrictions here.They may be adapted in any manner to the relevant requirements, e.g.according to the requirements of the paint manufacturer or itscustomers.

Dry color shade standard should be understood to mean an applied anddried paint standard, i.e. a cured or dried paint layer on a substrate,or any other dry color standard of arbitrary character. Dry paint shouldbe understood to mean an applied and dried paint. The dried paint mayalso be referred to as sprayed out paint, dry paint or cured paint.

Wet color shade standard should be understood to mean a wet paintstandard that is not dried or cured. Liquid paint should be understoodto mean a liquid paint that is not dried or cured.

Color shade standard may also be referred to as color standard.

Wet characterisation data or wet characterisation data set should beunderstood to mean the optical material parameters determined for eachconstituent of a given colorant system in a given liquid paint quality.

Dry characterisation data or dry characterisation data set should beunderstood to mean the optical material parameters determined for eachconstituent of a given colorant system in a given dry paint quality.

A prerequisite of any recipe prediction system is the knowledge of theoptical material parameters of all colored constituents of a givencolorant system for a given pigment mixture model. Optical materialparameters or characterisation data describe the properties of thepigments which are dispersed in a binder system of a particular paintquality. They are dependent on the wavelength and have to be determinedwithin the entire visible spectral range and have to be derived fromappropriate calibration panels. The calibration echelon to be preparedfor the determination of the optical material parameters by its natureis closely related to the radiative transfer model or pigment mixturemodel utilised. In the isotropic case (solid pigments) only twoparameters, namely the scattering and absorption coefficients, have tobe determined. When utilising a pigment mixture model to describe theanisotropic scattering properties of gonioapparent reflective pigments(special effect pigments) further wavelength-dependent materialparameters of the chosen model phase scattering function have to bederived. A specific set of calibration panels has to be prepared foreach pigment, whose reflectance is measured with a spectroradiometerwithin the wavelength and angle ranges of interest. The optical materialparameters are then derived numerically by adjusting the pigment mixturemodel to the experimental data of the calibration echelon in the senseof the L₂ norm.

The L₂-norm is a standard term in mathematical theory used to denote theEuclidean distance ∥x∥₂ between two positions x₁=(x_(1,x), x_(1,y),x_(1,z), . . . , x_(1,n)) and x₂=(x_(1,x), x_(1,y), x_(1,z), . . . ,x_(1,n)) in an n-dimensional space:

${x}_{2} = {\sqrt{\sum\limits_{i = 1}^{n}\left( {x_{1,i} - x_{2,i}} \right)^{2}} = {\sqrt{x_{1}^{T}x_{2}}.}}$

In three dimensions (n=3) the above equation simply reads∥x∥ ₂=√{square root over ((x _(1,x) −x _(2,x))²+(x _(1,y) −x _(2,y))²+(x_(1,z) −x _(2,z))²)}{square root over ((x _(1,x) −x _(2,x))²+(x _(1,y)−x _(2,y))²+(x _(1,z) −x _(2,z))²)}{square root over ((x _(1,x) −x_(2,x))²+(x _(1,y) −x _(2,y))²+(x _(1,z) −x _(2,z))²)}.

This distance measure can be used in the 3-dimensional colour space aswell as in an 31-dimensional reflectance space for a single spectrumcomprising the wavelength range 400 nm≦λ≦700 nm with a wavelength pitchof 10 nm. A generalization to angular dependent reflectance surfaces isstraightforward.

The standard methods in use for instrumental color development or batchshading are for instance described in:

Color Physics for Industry, edited by R. McDonald, Society of Dyers andColorists (Bradford, 1987) and Farbenphysik für industrielleAnwendungen, G. A. Klein (Springer, 2004).

In the relevant literature various model equations of different scopesof application and validity ranges are discussed. For an optimalmathematical treatment of the problem a differentiation is made betweenisotropic and anisotropic reflecting surface coatings. This division isalso adopted in the method of the present invention, although theisotropic case can be viewed as limiting case of the more general modelfor anisotropic reflecting surface coatings.

The theoretical approaches described below serve to elucidate themethodology and can be replaced by any thinkable form of a generaldiffusion equation describing the radiative transfer in particulatemedia. In this context it is worth mentioning the limitation of therepresented models to diluted systems, where the phenomenon of dependentscattering does not play an important role. For the case of highlypigmented or concentrated systems in the literature already other formsof the radiative transfer equations have been derived and discussed,whose solutions are considerably more complex and time-consuming from acomputational point of view than those approaches described below.

The optical material parameters of the selected approximation of theradiative transfer equation have to be determined by matching anappropriate pigment mixture model in the L₂ norm to the experimentallydetermined reflectance spectra or reflectance surfaces of a set ofcalibration panels and the corresponding liquid paints.

A sketch of a standard color development process flow is depicted inFIG. 1. The first process step usually consists of a microscopicanalysis of a gonioapparent color standard to be matched, whosepigmentation is unknown, to identify platelet-like special effectpigments 10. For solid color shades this pre-analysis is not required.The recipe calculation step is initiated by measuring the reflectanceproperties of the color standard within the visible spectral range undera single or multiple geometries by means of an appropriatespectrophotometer 12. This spectral target is matched by means of arecipe calculation program, which makes use of a pigment mixture modeland the associated optical material parameters derived in advance forthe set of available colorants 14, 16. The optimised formula is weighed18, sprayed, and dried 20 according to the necessities dictated by thechemistry of the binder system. Afterwards the obtained dry paint on thepanel is assessed visually and instrumentally in order to validate thequality of the match 22, 24. Due to process errors the sample will notperfectly match the color standard. However, if the match is within theagreed tolerances the color development process is terminated 26. If thematch is not acceptable a recipe correction analysis is carried out toreduce the residual color difference between color sample and colorstandard 28. Again the obtained corrected formula is weighed 30 andsprayed out and dried at elevated temperatures 32. Visual andinstrumental assessments of the reflectance properties complete theprocess step which has to be repeated until the color position of thesample is within the agreed tolerances 34, 36.

The number of cycles needed to match a given color standard depends onvarious factors as, e.g., the correction methodology, the degree ofstandardisation of the colorants, the performance of the pigment mixturemodel, and weighing and spraying variance. Also the accuracy of themeasurement process has inherent limitations.

Typical cycle numbers for solid colors are 3-4 and 5-8 for gonioapparentcolor shades, respectively.

Of all steps described so far the application and forced drying stepsrepresent the most time-consuming and expensive parts of the colordevelopment process. Typical time consumption for mixing a paintformulation, applying it onto a panel, and drying the prepared panel inan oven is about 90 to 120 minutes. The color development process couldbe designed to be more efficient if at least part of the recipecorrection steps could be carried out by measurement of liquid paint,eliminating the application and baking process steps. Thetime-consumption for a liquid paint measurement step is of the order of15 minutes. This change of paradigms can be accomplishedstraightforwardly if a liquid standard exists and the wet-to-drycorrelation is predictable. Unfortunately, this ideal situation is notapplicable to the color development process in coloristic laboratories,where wet standards in general are not available.

Therefore it is a specific advantage of the present invention to providea new process using a virtual wet standard which allows to switch from adry to a wet target in color development process. Prerequisite is theavailability of a dry as well as a wet characterisation data set thathave been prepared prior to the shading process for the given colorantsystem. Most preferred the dry and the wet characterisation data setshave been prepared and processed based on congruent blend patterns forboth dry and liquid paint materials. In particular good results can beobtained, if the model error for the dry and wet characterisation datasets can be kept almost the same. In such a case the performance ofcorrection steps carried out in the wet is in good agreement with theperformance of the corresponding sprayed-out paints of the standardcorrection procedure.

In step A) of the process of the present invention the dry color shadestandard is measured. For example, the reflectance spectrum of the drycolor shade standard to be matched is measured. Measuring can be donewith a spectrophotometer at a single measuring geometry (as, e.g.,45°/0° or d/8°) for solid color shades and at multiple measuringgeometries by means of a goniospectrophotometer suited for specialeffect color shades.

Generally, the corresponding color coordinates as, e.g., the triplet oftristimulus values or the L*, a*, b* values of the more uniform CIELabcolor space can be used in the present invention instead of using thereflectance spectra, i.e. instead of a spectral match criterion a colorspace match criterion can also be applied.

The color coordinates, e.g., the triplet of tristimulus values or theL*, a*, b* values of the CIELab color space, can be derived from themeasured reflectance spectra in a way well-known to a person skilled inthe art or can be measured directly with an appropriate measurementdevice.

In step B) of the present invention a recipe for the dry color shadestandard is calculated based on the measurement result of step A) and onan appropriate radiative transfer model to describe the diffusion oflight through particulate media. This is done according to usual recipecalculation methods well known to a person skilled in the art based ondry characterisation data.

As explained already, a prerequisite of the recipe calculation is theknowledge of the optical material parameters of all colored constituentsof the available colorant system. They have to be determinedexperimentally in advance for any colorant of the colorant system bymeans of a calibration echelon. The respective calibration echelon to beproduced is of course closely connected to the radiative transfer modelutilized. In the isotropic case two material parameters have to bedetermined, namely the scattering and absorption coefficients,respectively. For this purpose at least two different blends ofdifferent coloristic behaviour have to be measured. The model explicitlyaccounting for the anisotropy of scattering events contains furtherwavelength-dependent material constants used for the parametrisation ofthe phase function. In case of a neural network model the opticalproperties of all pigments are hidden and captured in the weights of thenetwork structure.

In case of solid pigments the well-known Schuster-Kubelka-Munk ortwo-flux approximation to the general radiative transfer equation isusually adopted. Within the scope of the two-flux approximation a simplerelationship can be derived between the reflectance R_(ext)(λ) of anopaque surface coating and the scattering (S) and absorption (K)coefficients of the individual pigments:

${{R_{ext}(\lambda)} = {{\alpha\; r_{ext}} + \frac{\left( {1 - r_{ext}} \right)\left( {1 - r_{int}} \right){R_{int}(\lambda)}}{1 - {r_{int}{R_{int}(\lambda)}}}}},{where}$${R_{int}(\lambda)} = {1 + \frac{K(\lambda)}{S(\lambda)} - {\sqrt{\left( {1 + \frac{K(\lambda)}{S(\lambda)}} \right)^{2} - 1}.}}$

The external (r_(ext)) and internal (r_(int)) Saunderson coefficientscorrect for the reflection effects of the refractive index discontinuityat the air/paint interface. The parameter α must be set to one, if thespecular surface gloss component is included in the reflectance signal,and set to zero in case the surface gloss component is excluded from themeasurement signal. In case of a perfectly diffuse radiationdistribution within the pigmented layer the external (r_(ext)) andinternal (r_(int)) reflection coefficients only depend on the relativerefractive index n=n_(paint)/n_(air) of the paint and the surroundingair. For n=1.5 the following Saunderson coefficients r_(ext)=0.04 andr_(int)=0.6 can be estimated, respectively. In an intimate mixture modelthe scattering and absorption coefficients S and K are additivelycomposed of the individual contributions of the different species ofrespective concentration c_(i):

${K = {\sum\limits_{i = 1}^{N}{c_{i}k_{i}}}},{S = {\sum\limits_{i = 1}^{N}{c_{i}s_{i}}}},$

The individual wavelength-dependent optical material parameters k_(i)and s_(i) have to be derived experimentally from the spectralreflectance data of all blends defining the calibration echelon.

This phenomenological radiative transfer model for isotropic scatteringparticulate media can be replaced by any N- or multi-flux approximationof the general radiative transfer equation, where the integration ofthis equation defines the scope of the application and the accuracy ofthe derived solution. For non-hiding films the inclusion of collimatedradiation fluxes improve the quality of the solution considerably. Theformalism can also be extended to stratified media with an arbitrarynumber of optically different layers.

Within the Schuster-Kubelka-Munk two-flux approximation for non-hidingsurface coatings the reflectance is given by the expression

${{R\left( {x,K,S} \right)} = \frac{1 - {r_{O}\left\lbrack {a - {b\;{\coth({bSx})}}} \right\rbrack}}{a - r_{O} + {b\;{\coth({bSx})}}}},$where x denotes the geometrical film thickness. The quantities a and bare related to the introduced scattering and absorption coefficients bythe relations

${a = {1 + \frac{K}{S}}},{b = {\sqrt{a^{2} - 1} = {\sqrt{\frac{K}{S}\left( {\frac{K}{S} + 2} \right)}.}}}$

The quantity r_(o) denotes the reflectance of the background.

As an example to illustrate the procedure for an alternate and moreefficient colour development process proposed in the present patentserves the azimuth-independent form of the radiative transfer equation

${{\mu\frac{\mathbb{d}{I\left( {x,\mu} \right)}}{\mathbb{d}x}} = {{I\left( {x,\mu} \right)} - {\frac{\omega_{O}}{4\pi}{\int_{- 1}^{+ 1}{{\mathbb{d}\mu^{\prime}}{I\left( {x,\mu^{\prime}} \right)}{p\left( {\mu,\mu^{\prime}} \right)}}}} + {I_{inc}\frac{\omega_{O}}{4\pi}{\mathbb{e}}^{{- \kappa}\;{x/\mu_{O}}}}}},$in which I(x,μ) denotes the specific intensity at geometrical depth xwithin the pigmented plane-parallel layer and μ=cos⁻¹ θ the cosine ofthe polar angle θ (in analogy μ_(o) represents the cosine of the angleθ_(o) of incident light). The redistribution function p(μ,μ′) describesthe process of how radiation impinging on a pigment particle isdistributed over all directions in space. For isotropic scattering mediathe relation p(μ,μ′)=1 applies. In case of anisotropic scattering mediafor p(μ,μ′) an appropriate parametrised function has to be identified todescribe the characteristic scattering properties of the respectivepigments to a sufficient degree of accuracy. For numerical stability andperformance reasons the number of parameters of the redistributionfunction should kept as low as possible.

Further optical material parameters as the absorption coefficient α andthe scattering coefficient σ of a pigment particle have been condensedin the albedo

$\omega_{O} = \frac{\sigma}{{\sigma + \kappa}\;}$of single-particle scattering. The albedo ω_(o) can be interpreted asprobability for scattering of light impinging on a particle. The opticalmaterial parameters (α,σ) are defined slightly differently than theanalogous quantities (K,S) of the phenomenological two-flux model ofSchuster-Kubelka-Munk and are therefore differentiated in notation. Theboundary conditions of the scattering problem as the refractive indexdiscontinuity at the air/paint interface as well as the reflectiveproperties of the background have to be accounted for explicitly whenintegrating the radiative transfer equation. Within the framework of theformalism also multi-layer models can be treated.

Empirical approaches for computer-aided colour matching based onartificial neural networks (ANNs) have also been devised in theliterature (WO 02/063556 A2, WO 02/063557 A2). In this model-free ANNapproach the neural network takes the role of the traditional radiativetransfer model. Networks of appropriately chosen topology are trained bymeans of a representative set of training panels. If the training set ischosen carefully the network should develop the capability to generaliseand interpolate with desired degree of accuracy. The performance of atrained ANN has to be validated by means of an independent set of testpanels.

In step B) of the present invention a recipe for the dry color shadestandard can also be identified, for example, from a database, based onthe measurement result of step A).

The database usually contains color recipes and the correspondingmeasured color data, i.e. the measured reflection spectra and/or thecolor coordinates. Usually those databases are used in vehicle repaircoating business by end-users as, e.g., in a repair body shop. Thedatabases usually contain a number of pre-developed color formulas basedon a defined colorant system, i.e. a defined assortment of colorants.The measured reflectance spectra and/or the color coordinates of eachcolor formula are also stored in the database. Identification of asuitable color formulation is carried out on the basis of the storedreflectance data and/or the color coordinates as selection criterion.

In step C) of the process of the present invention a virtual wet colorshade standard is generated based on the recipe for the dry color shadestandard calculated or identified in step B), wherein the virtual wetcolor shade standard is generated with wet characterisation data. Thewet characterisation data have been determined in advance in the sameway as explained above for determination of the dry characterisationdata and also stored in a database. The virtual wet standard can beprovided in form of a synthesised reflectance spectrum or in form of thecorresponding color coordinates derived thereof.

The details of creating the virtual wet standard shall be explainedbelow.

In color development four sources of error may have a significant impacton the performance of an instrumentally aided matching process: (i) thecapability error (color gamut), (ii) the model mismatch error(approximation), (iii) random errors (sample preparation, measurement,etc.), and (iv) bias errors (process mistakes, instrument scales, etc.).color match error=capability error+model mismatch error+randomerror+bias error

The capability error occurs if adjustment of the amounts of ingredientsin a color formula is not capable of an isomeric match to a colorstandard. The color gamut of the color formula does not contain thecolor position of the standard. If the residual color difference exceedsthe agreed tolerance, the best match will be unacceptable. Capabilityerrors can only be eliminated by choosing the right pigmentation in aformulation. If the right pigments are not available in a given colorantsystem, an isomeric match is not feasible.

The second error source of model mismatch in general is non-zero anddenotes the color difference between a synthesised reflectance spectrumof a color formula and the corresponding experimentally measuredreflectance spectrum of the sprayed-out panel. This is a measure of theperformance of a pigment mixture model and can be influenced by choosingan appropriate radiative transfer model and optimising the associatedmodel parameters.

Random errors are always present in practical sample preparation andmeasurement applications and can be considered to comprise the totalityof all process variations affecting a sample prepared to represent acolor formula. Typical components for this error category are tint,mixing, spraying, and measurement variations. The impact of such errorscan only be minimised by carefully analysing and designing the process.

The fourth category of bias or special cause errors comprises allsamples corrupted by true process mistakes and misadjustment ofmeasurement equipment. Such errors represent a challenge to therobustness of the color development process and have to be avoided byimplementing appropriate control strategies.

If the model error of the dry and wet characterisation data sets iscomparable, the matched formula c_(d) in the dry can be utilised tosynthesise a reflectance spectrum in the wet almost resembling thecorresponding reflectance spectrum of the physical wet standard.Therefore, this reflectance spectrum of a virtual wet standard may serveas a new target in the color development process. Part of the colordevelopment process can now be carried out in the wet. The performanceof the concept of virtual wet standards is expected to be efficient inthose cases, where characterisation data based on congruent blendpatterns for both dry and liquid paint materials have been prepared andprocessed. Only in such cases the model error is expected to cancel out.Otherwise fidelity of the methodology will deteriorate with increasingdeviation from consistency between dry and wet blend patterns.

The first step in color development is the determination of an isomericmatch by means of a recipe calculation program. If the chosen colorantassortment contains the right pigments and an isomeric match isfeasible, the measured reflectance spectrum of the standard and thepredicted reflectance spectrum of the selected set of ingredients arealways in good agreement with each other (see FIG. 3). However, if thepredicted formula is sprayed-out due to the impact of process errorsthere will always be an appreciable color difference between the colorstandard and the sprayed-out paint formula being larger than betweenstandard and predicted spectrum.

If the paint system used is also characterised in the wet using the sameor similar blends to those which have been used to generate the drycharacterisation data set, then the model error of both dry and wetcharacterisation data sets is about the same and there is a high chanceto match the unknown wet standard quite well by using the formula of thedry prediction and synthesise a corresponding wet spectrum with the wetcharacterisation data. This synthesised reflectance spectrum can servein the subsequent recipe correction steps as the new virtual wetstandard. This virtual wet color standard will always be close to thephysical wet standard, which means that a significant part of the recipecorrection steps can now be carried out in the wet which is supposed tobe much cheaper and quicker than the standard procedure based onsprayed-out paints.

Finally a virtual wet standard can be created which serves as wetstandard for the following shading step or steps. Therefore, existenceof a physical wet standard is not necessary.

In step D) of the process of the present invention the virtual wet colorshade standard is matched. This is done according to the usual procedureof color matching. Therefore, according to one embodiment the method ofthe present invention, in particular step D), further comprises thesteps E) to G).

According to step E) a paint is prepared based on the recipe for the drycolor shade standard calculated or identified in step B). The liquidpaint is then measured according to step F). When measuring thereflectance spectrum of the liquid paint well-known methods and devicesfor measuring liquid paint films can be used. A method for measuringoptical parameters on liquid paints is disclosed, for example, in U.S.Pat. No. 6,583,878, where a liquid paint is applied to a continuouslymoving cylindrical support. A film of the liquid paint is formed on thecylindrical support and its optical parameters can be measured. Also, inDE 2525701 a method is described, wherein a continuous thin liquid filmis formed from the paint to be measured. The liquid film may be a filmmoving with the support or with a laminar flow over a support. In thefirst case the support is a measuring disk that is rotatable about ahorizontal axis, and in the second case it is a plate-like body havingan approximately vertical surface.

Then the liquid paint is assessed to verify whether it is within arequired tolerance compared with the virtual wet standard (step G). Theassessment of the quality of a match can be made strictly visually orinstrumentally, or a combination of both approaches may be utilised. Incase of an instrumental assessment depending on the area of application(as, e.g., Refinish, Industrial or OEM coatings) and associatedacceptance solid various metrics may serve as a termination criterionfor the color development process. Typically the residual colordifference in a uniform color space (as, e.g., CIELab-76 or DIN-99) or aspecific color difference formula (as, e.g., CIE94 or CIEDE2000) isadopted for this purpose, where a threshold value is agreed onseparating accepted and rejected color regions. In case of gonioapparentcolors a generalisation of the formalism has to be made to properlyaccount for the angular dependence of the color appearance.

If the liquid paint composition is not within a requested tolerance, acorrected recipe for the liquid paint composition is calculatedaccording to step H). Then again a paint composition is preparedaccording to the corrected recipe for the liquid paint compositioncalculated in step H) according to step I). The liquid paint prepared instep I) is then measured (step J) and again the quality of match isassessed by comparing the measurement result with the virtual wet colorstandard (step K). Steps H) to K) are repeated until the liquid paintcomposition is within a requested tolerance.

If the liquid paint composition prepared in step E) or I) is within arequested tolerance the paint composition prepared in step E) or I) isapplied to a substrate and dried (step M).

Then the quality of match is assessed by comparing the dried paintcomposition with the dry color shade standard (step N). If the driedpaint composition is not within a requested tolerance a corrected recipefor the dried paint composition is calculated (step O). Then again apaint composition is prepared according to the corrected recipe (stepP). The paint composition is applied and dried (step R) and the qualityof match is assessed by comparing the dried paint composition the drycolor shade standard (step R). Steps O) to R) are repeated until thedried paint composition is within a requested tolerance.

It goes without saying that the order of the steps of the method of thepresent invention is not strictly fixed, but can be changed according tothe knowledge of a person skilled in the art.

The color development process according to the present invention isdepicted in FIGS. 2A and 2B in form of flow diagrams. The first steps upto the calculation of the on-load position of a dry panel 40-46 areidentical to the standard color development process displayed in FIG. 1.Then using the predicted formula for the dry standard, the virtual wetstandard reflectance data is calculated by utilising the correspondingwet characterisation data set 48. Hence, the color development processcan be switched from the dry to the wet target approach. The mixedformula of the wet prediction is measured and instrumentally correctedin the wet until the virtual liquid target is met within the agreedspecifications 50-54, 62-68. For the final liquid formula a panel issprayed-out and compared to the physical dry target (dry color shadestandard) 56, 58, 70, 72. In case of almost equal model errors theexpected residual color difference should also be within the agreedspecifications or very close to the target area. If this is not the casefurther correction steps in the dry versus the dry color shade standardhave to be carried out until the target area is met 74-82. This part ofthe modified color development process again is the same as in thestandard color development process.

The invention can be used in all areas of application, where colors haveto be developed or batches have to be shaded as, for example, inautomotive and industrial coatings applications. In automotive coatingsthe method can be used for OEM coatings as well as refinish coatings as,e.g., in color laboratories, in refinish body shops, in the paintmanufacturing process, and in standardisation of paints orstandardisation of pigment pastes.

The process is applicable to color shade standards of unknown or ofknown pigmentation, shading of solid and metallic colors can beperformed.

The present invention provides a method for color matching, whereincorrection steps usually performed with dry paints (dry panels) can nowbe replaced by correction steps using liquid paints. Hence, the methodreduces the number of tinting steps based on the dry color developmentprocess and the cycle time considerably.

Therefore, the matching method of the present invention is a moreefficient, time and cost saving method compared with usual known methodsfor color matching.

The invention is explained more detailed in the following example.

EXAMPLE

The efficiency of the devised modified color development process isdemonstrated making use of an example of a solid color shade. This solidcolor shade has to be matched using a given assortment of tints whichhave been characterised in the dry and in the wet using identical blendpatterns. For the example to be discussed below dry and wet targets (dryand wet color shade standards) are known so that the performance of thedried paint and the liquid paint can be compared directly for a colordevelopment carried with liquid paints.

The relevant reflectance data are depicted in FIGS. 4A and 4B. Thediagram of FIG. 4A displays the measured reflectance spectrum ofstandard 2003 of the RAL 841-GL collection of glossy industry colorsalong with the predicted reflectance spectrum of an optimisedformulation c=(c₁, c₂, . . . , c_(N))^(T) for a typical solvent-basedRefinish paint quality. With the exception of the long wavelength rangeabove 630 nm both spectra are almost congruent. In the diagram of FIG.4B the reflectance spectrum synthesised by means of the wetcharacterisation data set for the formula c optimised for the drycharacterisation data set is displayed. This synthesised reflectancespectrum represents the virtual wet standard for the color developmentsteps in the wet. For comparison purposes the diagram of FIG. 4B alsodisplays the true physical wet standard. A close scrutiny of the diagramof FIG. 4B reveals that the agreement of both reflectance spectracompares favourably to the two corresponding dry spectra shown in thediagram of FIG. 4A.

FIG. 5 displays the residual color difference data for each correctionstep of the color development process in the wet with the virtual wetstandard serving as the standard. The color development processterminates after the second correction step. Along with the wet colordevelopment data for each correction step corresponding residual colordifferences of each liquid paint sample to the physical wet standard andthe sprayed-out and dried paint against the dry standard are displayed.The data clearly corroborate the assertion that correction steps usuallycarried in the dry can be replaced by correction steps in the wet, ifthe model error for the dry and wet characterisation data sets can bekept almost the same. In such a case the performance of correction stepscarried out in the wet is in good agreement with the performance of thecorresponding sprayed-out panels of the standard correction procedure.

I claim:
 1. Method for matching the color of a dry color shade standard,said method comprising the steps of: A) Measuring the dry color shadestandard, B) Calculating a recipe for the dry color shade standard, oridentifying a matching recipe for the dry color shade standard, C)Generating a virtual wet color shade standard based on the recipe forthe dry color shade standard calculated or identified in step B),wherein the virtual wet color shade standard is generated with wetcharacterisation data, D) Matching the virtual wet color shade standard,E) Preparing a paint composition according to the recipe for the drycolor shade standard calculated or identified in step B), F) Measuringthe liquid paint composition prepared in step E), G) Assessing thequality of match by comparing the measurement result of step F) with thevirtual wet color shade standard generated in step C), H) If the liquidpaint composition prepared in step E) is not within a requestedtolerance, calculating a corrected recipe for said liquid paintcomposition, I) Preparing a paint composition according to the correctedrecipe for the liquid paint composition calculated in step H), J)Measuring the liquid paint composition prepared in step I), K) Assessingthe quality of match by comparing the measurement result of step J) withthe virtual wet color shade standard generated in step C), L) Repeatingsteps H) to K) until the liquid paint composition is within a requestedtolerance, M) If the liquid paint composition prepared in step E) or I)is within a requested tolerance, applying the paint composition preparedin step E) or I) to a substrate and drying the paint composition, N)Assessing the quality of match by comparing the dried paint compositionwith the dry color shade standard, O) Calculating a corrected recipe forthe dried paint composition, if the dried paint composition is notwithin a requested tolerance, P) Preparing a paint composition accordingto the corrected recipe for the dried paint composition calculated instep O), Q) Applying the paint composition prepared in step P) to asubstrate and drying the paint composition, R) Assessing the quality ofmatch by comparing the dried paint composition with the dry color shadestandard, and S) Repeating steps O) to R) until the dried paintcomposition is within a requested tolerance.
 2. The method of claim 1,wherein in step A) the reflectance spectrum is measured.
 3. The methodof claim 1, wherein in step A) the color coordinates are measured orderived from the measured reflectance spectrum.
 4. The method of any oneof claims 1 to 3, wherein the recipe for the dry color shade standard iscalculated or the matching recipe is identified on basis of drycharacterisation data.
 5. The method of claim 4, wherein the wetcharacterisation data and the dry characterisation data are based oncongruent blend patterns.
 6. The method of any one of claims 1 to 5,wherein the virtual wet color shade standard is generated in form of areflectance spectrum.
 7. The method of any one of claims 1 to 5, whereinthe virtual wet color shade standard is generated in form of colorcoordinates.
 8. The method of claim 1, wherein the quality of match isassessed instrumentally and/or visually.